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from langchain_core.tools import tool |
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import os |
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import io |
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import sys |
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import uuid |
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import base64 |
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import traceback |
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import contextlib |
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import tempfile |
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import subprocess |
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import sqlite3 |
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from typing import Dict, List, Any, Optional, Union |
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import numpy as np |
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import pandas as pd |
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import matplotlib.pyplot as plt |
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from PIL import Image |
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class CodeInterpreter: |
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def __init__(self, allowed_modules=None, max_execution_time=30, working_directory=None): |
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"""Initialize the code interpreter with safety measures.""" |
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self.allowed_modules = allowed_modules or [ |
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"numpy", "pandas", "matplotlib", "scipy", "sklearn", |
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"math", "random", "statistics", "datetime", "collections", |
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"itertools", "functools", "operator", "re", "json", |
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"sympy", "networkx", "nltk", "PIL", "pytesseract", |
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"cmath", "uuid", "tempfile", "requests", "urllib" |
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] |
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self.max_execution_time = max_execution_time |
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self.working_directory = working_directory or os.path.join(os.getcwd()) |
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if not os.path.exists(self.working_directory): |
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os.makedirs(self.working_directory) |
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self.globals = { |
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"__builtins__": __builtins__, |
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"np": np, |
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"pd": pd, |
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"plt": plt, |
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"Image": Image, |
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} |
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self.temp_sqlite_db = os.path.join(tempfile.gettempdir(), "code_exec.db") |
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def execute_code(self, code: str, language: str = "python") -> Dict[str, Any]: |
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"""Execute the provided code in the selected programming language.""" |
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language = language.lower() |
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execution_id = str(uuid.uuid4()) |
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result = { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": "", |
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"stderr": "", |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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try: |
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if language == "python": |
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return self._execute_python(code, execution_id) |
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elif language == "bash": |
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return self._execute_bash(code, execution_id) |
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elif language == "sql": |
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return self._execute_sql(code, execution_id) |
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elif language == "c": |
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return self._execute_c(code, execution_id) |
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elif language == "java": |
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return self._execute_java(code, execution_id) |
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else: |
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result["stderr"] = f"Unsupported language: {language}" |
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except Exception as e: |
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result["stderr"] = str(e) |
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return result |
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def _execute_python(self, code: str, execution_id: str) -> dict: |
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output_buffer = io.StringIO() |
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error_buffer = io.StringIO() |
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result = { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": "", |
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"stderr": "", |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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try: |
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exec_dir = os.path.join(self.working_directory, execution_id) |
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os.makedirs(exec_dir, exist_ok=True) |
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plt.switch_backend('Agg') |
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with contextlib.redirect_stdout(output_buffer), contextlib.redirect_stderr(error_buffer): |
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exec_result = exec(code, self.globals) |
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if plt.get_fignums(): |
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for i, fig_num in enumerate(plt.get_fignums()): |
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fig = plt.figure(fig_num) |
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img_path = os.path.join(exec_dir, f"plot_{i}.png") |
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fig.savefig(img_path) |
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with open(img_path, "rb") as img_file: |
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img_data = base64.b64encode(img_file.read()).decode('utf-8') |
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result["plots"].append({ |
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"figure_number": fig_num, |
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"data": img_data |
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}) |
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for var_name, var_value in self.globals.items(): |
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if isinstance(var_value, pd.DataFrame) and len(var_value) > 0: |
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result["dataframes"].append({ |
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"name": var_name, |
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"head": var_value.head().to_dict(), |
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"shape": var_value.shape, |
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"dtypes": str(var_value.dtypes) |
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}) |
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result["status"] = "success" |
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result["stdout"] = output_buffer.getvalue() |
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result["result"] = exec_result |
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except Exception as e: |
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result["status"] = "error" |
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result["stderr"] = f"{error_buffer.getvalue()}\n{traceback.format_exc()}" |
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return result |
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def _execute_bash(self, code: str, execution_id: str) -> dict: |
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try: |
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completed = subprocess.run( |
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code, shell=True, capture_output=True, text=True, timeout=self.max_execution_time |
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) |
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return { |
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"execution_id": execution_id, |
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"status": "success" if completed.returncode == 0 else "error", |
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"stdout": completed.stdout, |
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"stderr": completed.stderr, |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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except subprocess.TimeoutExpired: |
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return { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": "", |
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"stderr": "Execution timed out.", |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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def _execute_sql(self, code: str, execution_id: str) -> dict: |
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result = { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": "", |
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"stderr": "", |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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try: |
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conn = sqlite3.connect(self.temp_sqlite_db) |
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cur = conn.cursor() |
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cur.execute(code) |
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if code.strip().lower().startswith("select"): |
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columns = [description[0] for description in cur.description] |
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rows = cur.fetchall() |
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df = pd.DataFrame(rows, columns=columns) |
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result["dataframes"].append({ |
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"name": "query_result", |
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"head": df.head().to_dict(), |
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"shape": df.shape, |
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"dtypes": str(df.dtypes) |
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}) |
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else: |
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conn.commit() |
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result["status"] = "success" |
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result["stdout"] = "Query executed successfully." |
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except Exception as e: |
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result["stderr"] = str(e) |
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finally: |
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conn.close() |
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return result |
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def _execute_c(self, code: str, execution_id: str) -> dict: |
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temp_dir = tempfile.mkdtemp() |
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source_path = os.path.join(temp_dir, "program.c") |
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binary_path = os.path.join(temp_dir, "program") |
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try: |
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with open(source_path, "w") as f: |
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f.write(code) |
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compile_proc = subprocess.run( |
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["gcc", source_path, "-o", binary_path], |
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capture_output=True, text=True, timeout=self.max_execution_time |
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) |
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if compile_proc.returncode != 0: |
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return { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": compile_proc.stdout, |
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"stderr": compile_proc.stderr, |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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run_proc = subprocess.run( |
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[binary_path], |
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capture_output=True, text=True, timeout=self.max_execution_time |
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) |
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return { |
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"execution_id": execution_id, |
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"status": "success" if run_proc.returncode == 0 else "error", |
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"stdout": run_proc.stdout, |
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"stderr": run_proc.stderr, |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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except Exception as e: |
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return { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": "", |
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"stderr": str(e), |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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def _execute_java(self, code: str, execution_id: str) -> dict: |
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temp_dir = tempfile.mkdtemp() |
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source_path = os.path.join(temp_dir, "Main.java") |
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try: |
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with open(source_path, "w") as f: |
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f.write(code) |
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compile_proc = subprocess.run( |
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["javac", source_path], |
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capture_output=True, text=True, timeout=self.max_execution_time |
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) |
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if compile_proc.returncode != 0: |
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return { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": compile_proc.stdout, |
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"stderr": compile_proc.stderr, |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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run_proc = subprocess.run( |
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["java", "-cp", temp_dir, "Main"], |
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capture_output=True, text=True, timeout=self.max_execution_time |
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) |
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return { |
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"execution_id": execution_id, |
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"status": "success" if run_proc.returncode == 0 else "error", |
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"stdout": run_proc.stdout, |
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"stderr": run_proc.stderr, |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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except Exception as e: |
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return { |
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"execution_id": execution_id, |
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"status": "error", |
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"stdout": "", |
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"stderr": str(e), |
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"result": None, |
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"plots": [], |
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"dataframes": [] |
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} |
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interpreter_instance = CodeInterpreter() |
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@tool |
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def execute_code_multilang(code: str, language: str = "python") -> str: |
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"""Execute code in multiple languages (Python, Bash, SQL, C, Java) and return results. |
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Args: |
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code (str): The source code to execute. |
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language (str): The language of the code. Supported: "python", "bash", "sql", "c", "java". |
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Returns: |
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A string summarizing the execution results (stdout, stderr, errors, plots, dataframes if any). |
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""" |
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supported_languages = ["python", "bash", "sql", "c", "java"] |
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language = language.lower() |
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if language not in supported_languages: |
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return f"❌ Unsupported language: {language}. Supported languages are: {', '.join(supported_languages)}" |
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result = interpreter_instance.execute_code(code, language=language) |
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response = [] |
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if result["status"] == "success": |
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response.append(f"✅ Code executed successfully in **{language.upper()}**") |
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if result.get("stdout"): |
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response.append( |
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"\n**Standard Output:**\n```\n" + result["stdout"].strip() + "\n```" |
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) |
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if result.get("stderr"): |
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response.append( |
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"\n**Standard Error (if any):**\n```\n" |
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+ result["stderr"].strip() |
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+ "\n```" |
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) |
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if result.get("result") is not None: |
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response.append( |
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"\n**Execution Result:**\n```\n" |
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+ str(result["result"]).strip() |
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+ "\n```" |
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) |
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if result.get("dataframes"): |
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for df_info in result["dataframes"]: |
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response.append( |
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f"\n**DataFrame `{df_info['name']}` (Shape: {df_info['shape']})**" |
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) |
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df_preview = pd.DataFrame(df_info["head"]) |
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response.append("First 5 rows:\n```\n" + str(df_preview) + "\n```") |
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if result.get("plots"): |
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response.append( |
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f"\n**Generated {len(result['plots'])} plot(s)** (Image data returned separately)" |
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) |
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else: |
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response.append(f"❌ Code execution failed in **{language.upper()}**") |
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if result.get("stderr"): |
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response.append( |
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"\n**Error Log:**\n```\n" + result["stderr"].strip() + "\n```" |
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) |
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return "\n".join(response) |
